Dynamic Network User Equilibrium with State-Dependent Time Lags

This paper recasts the Friesz et al. (1993) measure theoretic model of dynamic network user equibrium as a controlled variational inequality problem involving Riemann integrals. This restatement is done to make the model and its foundations accessible to a wider audience by removing the need to have a background in functional analysis. Our exposition is dependent on previously unavailable necessary conditions for optimal control problems with state-dependent time lags. These necessary conditions, derived in an Appendix, are employed to show that a particular variational inequality control problem has solutions that are dynamic network user equilibria. Our analysis also shows that use of proper flow propagation constraints obviates the need to explicitly employ the arc exit time functions that have complicated numerical implementations of the Friesz et al. (1993) model heretofore. We close by describing the computational implications of numerically determining dynamic user equilibria from formulations based on state-dependent time lags.     

A survey of approaches to automatic schema matching

Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component. Received: 5 February 2001 / Accepted: 6 September 2001 Published online: 21 November 2001     

Making Sense of Memory.

The current work explores how people make recognition and belief judgments in the presence of obvious repetition primes. In two experiments, subjects received a 200-ms prime ("cheetah"), either before or after reading a trivia question ("What is the fastest animal?") but always before being presented with the target answer ("cheetah"). Results showed that repetition priming decreased "old" claims (Recognition - Experiment 1), while it increased truth claims (Belief - Experiment 2). Furthermore, repetition prime placement affected recognition but not belief. Combined, these results suggest that dissociations in memory performance are a natural outcome of task and processing demands and reflect the dynamic, flexible nature of memory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Robust H∞ stabilization via parametrized Lyapunovbounds

The parametrized Lyapunov bounding technique of Haddad and Bernstein (1991, 1993, 1995) is extended to include an H_∞ -disturbance attenuation constraint. The results presented in this paper provide a framework for designing fixed-order (i.e., full- and reduced-order) controllers that guarantee robust H₂ and H_∞ performance in the presence of structured constant real parameter variations in the state space model     

Robust controller synthesis via shifted parameter-dependentquadratic cost bounds

Parameterized Lyapunov bounds and shifted quadratic guaranteed cost bounds are merged to develop shifted parameter-dependent quadratic cost bounds for robust stability and robust performance. Robust fixed-order (i.e., full- and reduced-order) controllers are developed based on new shifted parameter-dependent bounding functions. A numerical example is presented to demonstrate the effectiveness of the proposed approach     

An Exploratory Examination of Student Attitudes Toward "Impaired" Peers in Clinical Psychology Training Programs.

Do psychology students view their training programs as doing enough to appropriately identify, accommodate, and possibly dismiss students who manifest significant impairment? This study reports the general findings of an exploratory survey distributed to clinical psychology graduate students. Overall, students viewed impairment as a highly sensitive and inadequately addressed issue. Students commonly reported frustration with and concern for impaired colleagues. A few respondents indicated that the terms impaired and problem student were insensitive and that greater attention needed to be given to "impaired" training contexts. Implications regarding formal standards for interpersonal functioning and programmatic supports for students are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The optimal projection equations for fixed-order dynamic compensation

First-order necessary conditions for quadratically optimal, steady-state,fixed-order dynamic compensation of a linear, time-invariant plant in the presence of disturbance and observation noise are derived in a new and highly simplified form. In contrast to the pair of matrix Riccati equations for the full-order LQG case, the optimal steady-state fixed-order dynamic compensator is characterized by four matrix equations (two modified Riccati equations and two modified Lyapunov equations) coupled by a projection whose rank is precisely equal to the order of the compensator and which determines the optimal compensator gains. The coupling represents a graphic portrayal of the demise of the classical separation principle for the reduced-order controller case.     

Manifold Learning: Generalization Ability and Tangent Proximity

One of the ultimate goals of Manifold Learning (ML) is to reconstruct an unknown nonlinear low-dimensional Data Manifold (DM) embedded in a high-dimensional observation space from a given set of data points sampled from the manifold. We derive asymptotic expansion and local lower and upper bounds for the maximum reconstruction error in a small neighborhood of an arbitrary point. The expansion and bounds are defined in terms of the distance between tangent spaces to the original DM and the Reconstructed Manifold (RM) at the selected point and its reconstructed value, respectively. We propose an amplification of the ML, called Tangent Bundle ML, in which proximity is required not only between the DM and RM but also between their tangent spaces. We present a new geometrically motivated Grassman & Stiefel Eigenmaps algorithm that solves this problem and gives a new solution for the ML also.     

Relations between anxiety sensitivity, distress tolerance, and fear reactivity to bodily sensations to coping and conformity marijuana use motives among young adult marijuana users.

The present investigation examines anxiety sensitivity, distress tolerance, and fear reactivity to bodily sensations in relation to Coping and Conformity marijuana use motives among a sample of young adult marijuana users (n = 135; 46.7% women; Mage = 20.45, SD = 5.0). After controlling for current marijuana use frequency (past 30 days), daily cigarette smoking rate, average volume of alcohol used over the past year, negative affectivity, and other marijuana use motives, anxiety sensitivity was significantly and uniquely associated with Coping and Conformity motives for marijuana use. Distress tolerance evidenced significant and unique incremental relations to Coping motives, whereas fear reactivity to bodily sensations was unrelated to any marijuana use motive. These results provide novel information related to the role of emotional sensitivity and tolerance factors as they pertain to specific types of motives for marijuana use among young adults. (PsycINFO Database Record (c) 2010 APA, all rights reserved)